Titlebook: Stochastic Systems: Modeling, Identification and Optimization I; Roger J.- B. Wets Book 1976Latest edition Springer-Verlag Berlin Heidelbe

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Panther

Edison Tsee is crucial for obtaining reliable results. On the other hand, utilization of excessively large simulation space significantly increases computation cost. This paper focuses on the optimization of a modeling range in the function of obtaining reliable and accurate results by minimization of modelin

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Stochastic Systems: Modeling, Identification and Optimization I

GEAR

On integrals in multi-output discrete-time Kalman-Bucy filtering,n is achieved through the exploitation of certain redundancies in the matrix Riccati equation. Although the main portion of this paper is concerned with stationary systems, our method also works in a more general setting. Hence we investigate what happens when the assumption of stationarity is remov

MARS

Entrance-exit distributions for Markov additive processes,form. Here, the same is obtained explicitly by using renewal theoretic arguments along with the results on Lévy systems of (.) given in ?inlar [4]. These results are useful in reliability theory and in the boundary theory of Markov processes.

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The choice of a stochastic model for a noise system,imensional distributions of . will be satisfactory approximations to those of .. We here investigate some cases to find when such an idealization can reasonably be expected to exist, and how to choose the system ..

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